Evidence map›Paper›PMID 34179356›Full record

ArticleJournal of patient experience2021

Using Electronic Medical Records and Health Claim Data to Develop a Patient Engagement Score for Patients With Multiple Chronic Conditions: An Exploratory Study.

Surachat Ngorsuraches, Semhar Michael, Nabin Poudel, Gemechis Djira, Emily Griese, Arielle Selya, Patricia Da Rosa

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of patient experience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Surachat NgorsurachesDepartment of Health Outcomes Research and Policy, Auburn University, Harrison School of Pharmacy, Auburn, AL, USA.ORCID https://orcid.org/0000-0002-2327-224X
Semhar MichaelDepartment of Mathematics and Statistics, Jerome J. Lohr College of Engineering, South Dakota State University, Brookings, SD, USA.
Nabin PoudelDepartment of Health Outcomes Research and Policy, Auburn University, Harrison School of Pharmacy, Auburn, AL, USA.
Gemechis DjiraDepartment of Mathematics and Statistics, Jerome J. Lohr College of Engineering, South Dakota State University, Brookings, SD, USA.
Emily GrieseDepartment of Pediatrics, University of South Dakota Sanford School of Medicine, Sanford Research, Sioux Falls, SD, USA.
Arielle SelyaDepartment of Pediatrics, University of South Dakota Sanford School of Medicine, Sanford Research, Sioux Falls, SD, USA.
Patricia Da RosaPopulation Health Evaluation Center, Office of Nursing Research, College of Nursing, South Dakota State University, Brookings, SD, USA.

Funding

Transdisciplinary approaches to American Indian and rural population health researchP20GM121341 · NIGMS · SANFORD RESEARCH/USD · PI PUUMALA, SUSAN E · 2017 to 2022
$11.8M
NIGMS NIH HHS P20 GM121341
6 · The paper itself

Abstract

The study objective was to (1) develop a statistical model that creates a novel patient engagement score (PES) from electronic medical records (EMR) and health claim data, and (2) validate this developed score using health-related outcomes and charges of patients with multiple chronic conditions (MCCs). This study used 2014-16 EMR and health claim data of patients with MCCs from Sanford Health. Patient engagement score was created based on selected patients' engagement behaviors using Gaussian finite mixture model. The PES was validated using multiple logistic and linear regression analyses to examine the associations between the PES and health-related outcomes, and hospital charges, respectively. Patient engagement score was generated from 5095 patient records and included low, medium, and high levels of patient engagement. The PES was a significant predictor for low-density lipoprotein, emergency department visit, hemoglobin A

Indexed as

electronic health records (EMR)multiple chronic conditions (MCC)patient activation measure (PAM)patient engagement score (PES)treatment outcome

Identifiers

PMID34179356
PMCPMC8205346

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.